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Key message <p>ATR-FTIR spectroscopy combined with statistical modelling provides accurate predictions of forest floor properties: total organic carbon, total nitrogen, total phosphorus and ash. Performance decreases in carbonate-rich samples, particularly for organic carbon and the carbon to nitrogen ratio; excluding such samples improves reliability. This makes ATR-FTIR a fast and sustainable complement to conventional chemical analyses for forest monitoring and nutrient cycling studies.</p> Context <p>Organic forest layers and their decomposition are essential for nutrient cycling, soil fertility, and carbon sequestration in forest ecosystems. While infrared spectroscopy is widely applied to assess physical and chemical attributes in soil samples, its effectiveness in evaluating forest floor samples remains poorly studied.</p> Aims <p>This study evaluated the efficacy of Attenuated Total Reflection Fourier Transform Infrared Spectroscopy (ATR-FTIR) to predict forest floor properties: total organic carbon, total nitrogen, and their ratio, total phosphorus, and ash content.</p> Methods <p>Forest floor material from a European network of forest plots was analyzed. Organic layers of <i>Pinus sylvestris</i><i>, L.,</i>&#xa0;<i>Quercus </i>spp., and <i>Fagus sylvatica</i> L.&#xa0;in monospecific and mixed forest stands were examined, differentiating between species and litter layers: undecomposed, intermediate decomposed, and humified. ATR-FTIR spectra (4000 to 400&#xa0;cm<sup>−1</sup>) were recorded and analyzed. A modified partial least-squares method and a Generalized Linear Mixed Model with cross-validation were used to develop equations and predictive models for forest floor properties, combining ATR-FTIR spectra with laboratory data.</p> Results <p>Accurate explanatory and predictive models were developed for forest floor samples using ATR-FTIR spectroscopy, highlighting its potential as a complementary or alternative tool to traditional chemical analyses. Total organic carbon predictions were more accurate when carbonate-containing samples were excluded from calibration.</p> Conclusions <p>ATR-FTIR provides a reliable alternative for assessing forest floor properties, supporting sustainable forest management by improving monitoring of nutrient cycling and carbon storage.</p>

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Integrated modelling approaches for estimating total organic carbon, total nitrogen, total phosphorus, and ash content in forest floor samples using ATR-FTIR spectroscopy

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月11日

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  • Ruth C. Martín-Sanz,
  • Marina Getino-Álvarez,
  • Valentín Pando,
  • Francisco Lafuente,
  • M. Belén Turrión

摘要

Key message

ATR-FTIR spectroscopy combined with statistical modelling provides accurate predictions of forest floor properties: total organic carbon, total nitrogen, total phosphorus and ash. Performance decreases in carbonate-rich samples, particularly for organic carbon and the carbon to nitrogen ratio; excluding such samples improves reliability. This makes ATR-FTIR a fast and sustainable complement to conventional chemical analyses for forest monitoring and nutrient cycling studies.

Context

Organic forest layers and their decomposition are essential for nutrient cycling, soil fertility, and carbon sequestration in forest ecosystems. While infrared spectroscopy is widely applied to assess physical and chemical attributes in soil samples, its effectiveness in evaluating forest floor samples remains poorly studied.

Aims

This study evaluated the efficacy of Attenuated Total Reflection Fourier Transform Infrared Spectroscopy (ATR-FTIR) to predict forest floor properties: total organic carbon, total nitrogen, and their ratio, total phosphorus, and ash content.

Methods

Forest floor material from a European network of forest plots was analyzed. Organic layers of Pinus sylvestris, L., Quercus spp., and Fagus sylvatica L. in monospecific and mixed forest stands were examined, differentiating between species and litter layers: undecomposed, intermediate decomposed, and humified. ATR-FTIR spectra (4000 to 400 cm−1) were recorded and analyzed. A modified partial least-squares method and a Generalized Linear Mixed Model with cross-validation were used to develop equations and predictive models for forest floor properties, combining ATR-FTIR spectra with laboratory data.

Results

Accurate explanatory and predictive models were developed for forest floor samples using ATR-FTIR spectroscopy, highlighting its potential as a complementary or alternative tool to traditional chemical analyses. Total organic carbon predictions were more accurate when carbonate-containing samples were excluded from calibration.

Conclusions

ATR-FTIR provides a reliable alternative for assessing forest floor properties, supporting sustainable forest management by improving monitoring of nutrient cycling and carbon storage.